Abstract

Inconsistency is commonplace in the real world in long-term memory and knowledge based systems. Managing inconsistency is considered a hallmark of the plasticity of human intelligence. Belief revision is an important mental process that underpins human intelligence. To facilitate belief revision, it is necessary to know the localities and contexts of inconsistency and how different types of inconsistency are clustered. In this paper, the author provides a formal definition of locality of inconsistency and describes how to identify clusters of inconsistent circumstances in a knowledge base. The results pave the way for a disciplined approach to manage knowledge inconsistency.

Article Preview

2. Knowledge Inconsistency Types

Since the process of identifying locality of inconsistency will be affected by various types of inconsistency to be encountered, it is necessary to know how many types of knowledge inconsistency we need to deal with. In our previous work, we have identified the following twelve types of inconsistency (Zhang, 2008, 2009, 2010b) which are briefly summarized as follows.